Issue |
ITM Web Conf.
Volume 71, 2025
International Conference on Mathematics, its Applications and Mathematics Education (ICMAME 2024)
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Article Number | 01014 | |
Number of page(s) | 11 | |
DOI | https://doi.org/10.1051/itmconf/20257101014 | |
Published online | 06 February 2025 |
Development of an Epidemiological Model with Transmission Matrix to Understand the Dynamics of Tuberculosis Spread
Mathematics Department, Faculty of Mathematic and Sciences, Universitas Tanjungpura, 78124 Indonesia
* Corresponding author: melianapasaribu@math.untan.ac.id
Tuberculosis remains a major challenge in the field of healthcare. The spread of tuberculosis depends on complex interactions between individuals within a population, involving factors such as mobility, physical contact, and age groups. Each age group has unique characteristics that influence how tuberculosis spreads among the population and how each group responds to the infection. To understand the dynamics of tuberculosis spread, an epidemiological model is required. This study aims to develop an epidemiological model based on a transmission matrix that can represent the pattern of tuberculosis spread within a population. The transmission matrix is used to describe the interactions between individuals and subpopulations, taking into account the transmission rate and incubation period. After building the model and transmission matrix, model calibration and validation are conducted. In this stage, model parameters are adjusted to ensure that the model can accurately replicate the observed epidemiological data. Subsequently, analysis is performed using the model and transmission matrix to understand the dynamics of disease spread, followed by interpretation of the results. The findings of this study indicate that the use of the transmission matrix provides valuable insights into the dynamics of tuberculosis spread and helps identify high-risk subpopulations.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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